Abstract: This article deals with the polymodal space in the field of computational creativity in neural networks. The object of research is a polymodal environment that integrates a series of heterogeneous codes to express a common idea, and the subject is the possibility of creating polymodal digital art using text and voice prompts in the generative network Midjourney. The aim of the study is to prove that computational creativity can be detected and described based on the results of iterations in the process of creating images, which in turn will allow us to talk about a complex polymodal system as a separate digital category of polymodality.
We used the continuous sampling method when collecting linguistic units as they occur in the analysis process; contextual analysis for the systematic identification and description of the verbal and non-verbal contexts. It was necessary to conduct an experiment with the generative network Midjourney to identify patterns in the creation of a graphic space through text and voice data input, and then compare and contrast the results of iterations with the original image.
The scientific novelty consists in the lack of research on the polymodal space in the context of neural networks and their generative ability. During the experiment, we obtained the following results: the term ‘polymodality’ in the context of the generative network Midjourney and its ‘digital art’ is due to the presence of three channels: verbal, visual and voice; tests have shown that the ability of the neural network to create images through prompt is at a high level, however, there are rough technical errors that do not allow users to fully approach the desired result when they generate an image; the summarization of the data allows us to talk about the presence of features of computational creativity in generative networks.

Abstract: The subject of the study is the content of personal meanings of greeting questions in the context of English communication formulas of Siri. The object of the study is the ability of the voice assistant to simulate spontaneous dialogue with a person and the adaptation of artificial intelligence to natural speech. The purpose of the study is to identify the features and level of Siri's language skills in the process of communicating with users in English. Such aspects of the topic as the problem of understanding that exists in two types of communication are considered in detail: 1) between a person and a person; 2) between a machine and a person; the use of stable communication formulas by artificial intelligence as responses to the question «How are you?»; determining the level and speech-making potential in the responses of the voice assistant. The following methods were used in the research: descriptive, comparative, contextual, comparative method and linguistic experiment. The scientific novelty is that the problems related to encoding the personal meanings of the Siri voice assistant have never been studied in detail in philology and linguistics. Due to the prevalence use of voice systems in various spheres of social and public life, there is a need to analyze errors in speech and describe communication failures in dialogues between voice assistants and users. The main conclusions of the study are: 1) the machine is not able to generate answers based on the experience of past impressions; 2) deviations from the norms of English speech etiquette in Siri's responses are insignificant, but often lead to communicative failures; 3) the one-sided encoding of personal meaning was found in the responses: from the machine to the person, but not vice versa.

Abstract: The article describes the analysis of the "spontaneous" dialogue of two Russian and foreign voice systems. The study is relevant because the possibilities of communication of the introduction spontaneously dialogue between Russian-speaking and foreign voice systems have not been studied by now. The objects of research have become two Russian-speaking systems – Alice by Yandex, voice assistant application by Sberbank; two English voice systems – Siri by Apple Ink and Google Assistant, including their Russian version. The choice is due to their popularity among native speakers of the Russian language, which was determined by the requests of these voice assistants on the Internet. The sampling period was from January 1, 2021 to December 20, 2022. Russian-speaking and English-speaking voice systems were selected by a continuous sampling method. The article draws conclusions, including about the communicative capabilities of Russian-speaking voice systems and foreign analogues with a built-in translation function into Russian. The scientific novelty is the analysis of "spontaneous" dialogic speech and the analysis of its compliance with the norms of the modern Russian language. At the end of the article there are results of the analysis of foreign phrases and expressions with a small number of variants are summarized to generate a response to the user based on materials from the corpus of the Russian language. Also, it is not uncommon to identify features of machine translation in foreign voice analogues, unlike Russian-speaking voice assistants.